3.2 The standard type hierarchy

Below is a list of the types that are built into Python. Extension
modules (written in C, Java, or other languages, depending on
the implementation) can define additional types. Future versions of
Python may add types to the type hierarchy (e.g., rational
numbers, efficiently stored arrays of integers, etc.).

Some of the type descriptions below contain a paragraph listing
`special attributes.' These are attributes that provide access to the
implementation and are not intended for general use. Their definition
may change in the future.

None

This type has a single value. There is a single object with this value.
This object is accessed through the built-in name None.
It is used to signify the absence of a value in many situations, e.g.,
it is returned from functions that don't explicitly return anything.
Its truth value is false.

NotImplemented

This type has a single value. There is a single object with this value.
This object is accessed through the built-in name NotImplemented.
Numeric methods and rich comparison methods may return this value if
they do not implement the operation for the operands provided. (The
interpreter will then try the reflected operation, or some other
fallback, depending on the operator.) Its truth value is true.

Ellipsis

This type has a single value. There is a single object with this value.
This object is accessed through the built-in name Ellipsis.
It is used to indicate the presence of the "..." syntax in a
slice. Its truth value is true.

Numbers

These are created by numeric literals and returned as results by
arithmetic operators and arithmetic built-in functions. Numeric
objects are immutable; once created their value never changes. Python
numbers are of course strongly related to mathematical numbers, but
subject to the limitations of numerical representation in computers.

Python distinguishes between integers, floating point numbers, and
complex numbers:

Integers

These represent elements from the mathematical set of whole numbers.

There are two types of integers:

Plain integers

These represent numbers in the range -2147483648 through 2147483647.
(The range may be larger on machines with a larger natural word
size, but not smaller.)
When the result of an operation would fall outside this range, the
result is normally returned as a long integer (in some cases, the
exception OverflowError is raised instead).
For the purpose of shift and mask operations, integers are assumed to
have a binary, 2's complement notation using 32 or more bits, and
hiding no bits from the user (i.e., all 4294967296 different bit
patterns correspond to different values).

Long integers

These represent numbers in an unlimited range, subject to available
(virtual) memory only. For the purpose of shift and mask operations,
a binary representation is assumed, and negative numbers are
represented in a variant of 2's complement which gives the illusion of
an infinite string of sign bits extending to the left.

The rules for integer representation are intended to give the most
meaningful interpretation of shift and mask operations involving
negative integers and the least surprises when switching between the
plain and long integer domains. Any operation except left shift,
if it yields a result in the plain integer domain without causing
overflow, will yield the same result in the long integer domain or
when using mixed operands.

Floating point numbers

These represent machine-level double precision floating point numbers.
You are at the mercy of the underlying machine architecture (and
C or Java implementation) for the accepted range and handling of overflow.
Python does not support single-precision floating point numbers; the
savings in processor and memory usage that are usually the reason for using
these is dwarfed by the overhead of using objects in Python, so there
is no reason to complicate the language with two kinds of floating
point numbers.

Complex numbers

These represent complex numbers as a pair of machine-level double
precision floating point numbers. The same caveats apply as for
floating point numbers. The real and imaginary parts of a complex
number z can be retrieved through the read-only attributes
z.real and z.imag.

Sequences

These represent finite ordered sets indexed by non-negative numbers.
The built-in function len()returns the
number of items of a sequence.
When the length of a sequence is n, the
index set contains the numbers 0, 1, ..., n-1. Item
i of sequence a is selected by a[i].

Sequences also support slicing: a[i:j]
selects all items with index k such that i<=k<j. When used as an expression, a slice is a
sequence of the same type. This implies that the index set is
renumbered so that it starts at 0.

Sequences are distinguished according to their mutability:

Immutable sequences

An object of an immutable sequence type cannot change once it is
created. (If the object contains references to other objects,
these other objects may be mutable and may be changed; however,
the collection of objects directly referenced by an immutable object
cannot change.)

The following types are immutable sequences:

Strings

The items of a string are characters. There is no separate
character type; a character is represented by a string of one item.
Characters represent (at least) 8-bit bytes. The built-in
functions chr()and
ord()convert between characters and
nonnegative integers representing the byte values. Bytes with the
values 0-127 usually represent the corresponding ASCII values, but
the interpretation of values is up to the program. The string
data type is also used to represent arrays of bytes, e.g., to hold data
read from a file.

(On systems whose native character set is not ASCII, strings may use
EBCDIC in their internal representation, provided the functions
chr() and ord() implement a mapping between ASCII and
EBCDIC, and string comparison preserves the ASCII order.
Or perhaps someone can propose a better rule?)

Unicode

The items of a Unicode object are Unicode code units. A Unicode code
unit is represented by a Unicode object of one item and can hold
either a 16-bit or 32-bit value representing a Unicode ordinal (the
maximum value for the ordinal is given in sys.maxunicode, and
depends on how Python is configured at compile time). Surrogate pairs
may be present in the Unicode object, and will be reported as two
separate items. The built-in functions
unichr()and
ord()convert between code units and
nonnegative integers representing the Unicode ordinals as defined in
the Unicode Standard 3.0. Conversion from and to other encodings are
possible through the Unicode method encode and the built-in
function unicode().

Tuples

The items of a tuple are arbitrary Python objects.
Tuples of two or more items are formed by comma-separated lists
of expressions. A tuple of one item (a `singleton') can be formed
by affixing a comma to an expression (an expression by itself does
not create a tuple, since parentheses must be usable for grouping of
expressions). An empty tuple can be formed by an empty pair of
parentheses.

Mutable sequences

Mutable sequences can be changed after they are created. The
subscription and slicing notations can be used as the target of
assignment and del (delete) statements.

There is currently a single intrinsic mutable sequence type:

Lists

The items of a list are arbitrary Python objects. Lists are formed
by placing a comma-separated list of expressions in square brackets.
(Note that there are no special cases needed to form lists of length 0
or 1.)

The extension module arrayprovides an
additional example of a mutable sequence type.

Mappings

These represent finite sets of objects indexed by arbitrary index sets.
The subscript notation a[k] selects the item indexed
by k from the mapping a; this can be used in
expressions and as the target of assignments or del statements.
The built-in function len() returns the number of items
in a mapping.

There is currently a single intrinsic mapping type:

Dictionaries

Theserepresent finite sets of objects indexed by
nearly arbitrary values. The only types of values not acceptable as
keys are values containing lists or dictionaries or other mutable
types that are compared by value rather than by object identity, the
reason being that the efficient implementation of dictionaries
requires a key's hash value to remain constant.
Numeric types used for keys obey the normal rules for numeric
comparison: if two numbers compare equal (e.g., 1 and
1.0) then they can be used interchangeably to index the same
dictionary entry.

Dictionaries are mutable; they can be created by the
{...} notation (see section 5.2.5, ``Dictionary
Displays'').

Theseare the types to which the function call
operation (see section 5.3.4, ``Calls'') can be applied:

User-defined functions

A user-defined function object is created by a function definition
(see section 7.5, ``Function definitions''). It should be
called with an argument
list containing the same number of items as the function's formal
parameter list.

Special attributes: func_doc or __doc__ is the
function's documentation string, or None if unavailable;
func_name or __name__ is the function's name;
func_defaults is a tuple containing default argument values for
those arguments that have defaults, or None if no arguments
have a default value; func_code is the code object representing
the compiled function body; func_globals is (a reference to)
the dictionary that holds the function's global variables -- it
defines the global namespace of the module in which the function was
defined; func_dict or __dict__ contains the
namespace supporting arbitrary function attributes;
func_closure is None or a tuple of cells that contain
binding for the function's free variables.

Of these, func_code, func_defaults, func_closure,
func_doc/__doc__, and
func_dict/__dict__ may be writable; the
others can never be changed. Additional information about a
function's definition can be retrieved from its code object; see the
description of internal types below.

A user-defined method object combines a class, a class instance (or
None) and any callable object (normally a user-defined
function).

Special read-only attributes: im_self is the class instance
object, im_func is the function object;
im_class is the class of im_self for bound methods,
or the class that asked for the method for unbound methods);
__doc__ is the method's documentation (same as
im_func.__doc__); __name__ is the method name (same as
im_func.__name__).
Changed in version 2.2:
im_self used to refer to the class that
defined the method.

Methods also support accessing (but not setting) the arbitrary
function attributes on the underlying function object.

User-defined method objects are created in two ways: when getting an
attribute of a class that is a user-defined function object, or when
getting an attribute of a class instance that is a user-defined
function object defined by the class of the instance. In the former
case (class attribute), the im_self attribute is None,
and the method object is said to be unbound; in the latter case
(instance attribute), im_self is the instance, and the method
object is said to be bound. For
instance, when C is a class which has a method
f(), C.f does not yield the function object
f; rather, it yields an unbound method object m where
m.im_class is C, m.im_func is f(), and
m.im_self is None. When x is a C
instance, x.f yields a bound method object m where
m.im_class is C, m.im_func is f(), and
m.im_self is x.

When an unbound user-defined method object is called, the underlying
function (im_func) is called, with the restriction that the
first argument must be an instance of the proper class
(im_class) or of a derived class thereof.

When a bound user-defined method object is called, the underlying
function (im_func) is called, inserting the class instance
(im_self) in front of the argument list. For instance, when
C is a class which contains a definition for a function
f(), and x is an instance of C, calling
x.f(1) is equivalent to calling C.f(x, 1).

Note that the transformation from function object to (unbound or
bound) method object happens each time the attribute is retrieved from
the class or instance. In some cases, a fruitful optimization is to
assign the attribute to a local variable and call that local variable.
Also notice that this transformation only happens for user-defined
functions; other callable objects (and all non-callable objects) are
retrieved without transformation. It is also important to note that
user-defined functions which are attributes of a class instance are
not converted to bound methods; this only happens when the
function is an attribute of the class.

Generator functions

A function or method which uses the yield statement (see
section 6.8, ``The yield statement'') is called a
generator function. Such a function, when called, always
returns an iterator object which can be used to execute the body of
the function: calling the iterator's next() method will
cause the function to execute until it provides a value using the
yield statement. When the function executes a
return statement or falls off the end, a
StopIteration exception is raised and the iterator will
have reached the end of the set of values to be returned.

Built-in functions

A built-in function object is a wrapper around a C function. Examples
of built-in functions are len() and math.sin()
(math is a standard built-in module).
The number and type of the arguments are
determined by the C function.
Special read-only attributes: __doc__ is the function's
documentation string, or None if unavailable; __name__
is the function's name; __self__ is set to None (but see
the next item).

Built-in methods

This is really a different disguise of a built-in function, this time
containing an object passed to the C function as an implicit extra
argument. An example of a built-in method is
alist.append(), assuming
alist is a list object.
In this case, the special read-only attribute __self__ is set
to the object denoted by list.

Classes

Class objects are described below. When a class object is called,
a new class instance (also described below) is created and
returned. This implies a call to the class's __init__() method
if it has one. Any arguments are passed on to the __init__()
method. If there is no __init__() method, the class must be called
without arguments.

Class instances

Class instances are described below. Class instances are callable
only when the class has a __call__() method; x(arguments)
is a shorthand for x.__call__(arguments).

Modules

Modules are imported by the import statement (see
section 6.12, ``The import statement'').
A module object has a namespace implemented by a dictionary object
(this is the dictionary referenced by the func_globals attribute of
functions defined in the module). Attribute references are translated
to lookups in this dictionary, e.g., m.x is equivalent to
m.__dict__["x"].
A module object does not contain the code object used to
initialize the module (since it isn't needed once the initialization
is done).

Special read-only attribute: __dict__ is the module's
namespace as a dictionary object.

Predefined (writable) attributes: __name__
is the module's name; __doc__ is the
module's documentation string, or
None if unavailable; __file__ is the pathname of the
file from which the module was loaded, if it was loaded from a file.
The __file__ attribute is not present for C modules that are
statically linked into the interpreter; for extension modules loaded
dynamically from a shared library, it is the pathname of the shared
library file.

Classes

Class objects are created by class definitions (see
section 7.6, ``Class definitions'').
A class has a namespace implemented by a dictionary object.
Class attribute references are translated to
lookups in this dictionary,
e.g., "C.x" is translated to "C.__dict__["x"]".
When the attribute name is not found
there, the attribute search continues in the base classes. The search
is depth-first, left-to-right in the order of occurrence in the
base class list.
When a class attribute reference would yield a user-defined function
object, it is transformed into an unbound user-defined method object
(see above). The im_class attribute of this method object is the
class for which the attribute reference was initiated.

Class attribute assignments update the class's dictionary, never the
dictionary of a base class.

A class object can be called (see above) to yield a class instance (see
below).

Special attributes: __name__ is the class name;
__module__ is the module name in which the class was defined;
__dict__ is the dictionary containing the class's namespace;
__bases__ is a tuple (possibly empty or a singleton)
containing the base classes, in the order of their occurrence in the
base class list; __doc__ is the class's documentation string,
or None if undefined.

Class instances

A class instance is created by calling a class object (see above).
A class instance has a namespace implemented as a dictionary which
is the first place in which
attribute references are searched. When an attribute is not found
there, and the instance's class has an attribute by that name,
the search continues with the class attributes. If a class attribute
is found that is a user-defined function object (and in no other
case), it is transformed into an unbound user-defined method object
(see above). The im_class attribute of this method object is
the
class of the instance for which the attribute reference was initiated.
If no class attribute is found, and the object's class has a
__getattr__() method, that is called to satisfy the lookup.

Attribute assignments and deletions update the instance's dictionary,
never a class's dictionary. If the class has a __setattr__() or
__delattr__() method, this is called instead of updating the
instance dictionary directly.

Class instances can pretend to be numbers, sequences, or mappings if
they have methods with certain special names. See
section 3.3, ``Special method names.''

Special attributes: __dict__ is the attribute
dictionary; __class__ is the instance's class.

Files

A fileobject represents an open file. File objects are
created by the open()built-in function,
and also by
os.popen(),
os.fdopen(), and the
makefile()method of socket objects (and perhaps by other functions or methods
provided by extension modules). The objects
sys.stdin,
sys.stdout and
sys.stderr are initialized to file objects
corresponding to the interpreter's standardinput, output
and error streams. See the Python Library
Reference for complete documentation of file objects.

Internal types

A few types used internally by the interpreter are exposed to the user.
Their definitions may change with future versions of the interpreter,
but they are mentioned here for completeness.

Code objects

Code objects represent byte-compiled executable Python code, or
bytecode.
The difference between a code
object and a function object is that the function object contains an
explicit reference to the function's globals (the module in which it
was defined), while a code object contains no context;
also the default argument values are stored in the function object,
not in the code object (because they represent values calculated at
run-time). Unlike function objects, code objects are immutable and
contain no references (directly or indirectly) to mutable objects.

Special read-only attributes: co_name gives the function
name; co_argcount is the number of positional arguments
(including arguments with default values); co_nlocals is the
number of local variables used by the function (including arguments);
co_varnames is a tuple containing the names of the local
variables (starting with the argument names); co_cellvars is
a tuple containing the names of local variables that are referenced by
nested functions; co_freevars is a tuple containing the names
of local variables that are neither local nor global; co_code
is a string representing the sequence of bytecode instructions;
co_consts is a tuple containing the literals used by the
bytecode; co_names is a tuple containing the names used by
the bytecode; co_filename is the filename from which the code
was compiled; co_firstlineno is the first line number of the
function; co_lnotab is a string encoding the mapping from
byte code offsets to line numbers (for details see the source code of
the interpreter); co_stacksize is the required stack size
(including local variables); co_flags is an integer encoding
a number of flags for the interpreter.

The co_cellvars and co_freevars are present in
Python 2.1 when nested scopes are not enabled, but the code itself
does not use or create cells.

The following flag bits are defined for co_flags: bit
0x04 is set if the function uses the "*arguments" syntax
to accept an arbitrary number of positional arguments; bit
0x08 is set if the function uses the "**keywords" syntax
to accept arbitrary keyword arguments; other bits are used internally
or reserved for future use; bit 0x10 is set if the function was
compiled with nested scopes enabled. Ifa
code object represents a function, the first item in
co_consts is the documentation string of the function, or
None if undefined.

Special read-only attributes: f_back is to the previous
stack frame (towards the caller), or None if this is the bottom
stack frame; f_code is the code object being executed in this
frame; f_locals is the dictionary used to look up local
variables; f_globals is used for global variables;
f_builtins is used for built-in (intrinsic) names;
f_restricted is a flag indicating whether the function is
executing in restricted execution mode;
f_lineno gives the line number and f_lasti gives the
precise instruction (this is an index into the bytecode string of
the code object).

Special writable attributes: f_trace, if not None, is a
function called at the start of each source code line (this is used by
the debugger); f_exc_type, f_exc_value,
f_exc_traceback represent the most recent exception caught in
this frame.

Traceback objects

Traceback objects represent a stack trace of an exception. A
traceback object is created when an exception occurs. When the search
for an exception handler unwinds the execution stack, at each unwound
level a traceback object is inserted in front of the current
traceback. When an exception handler is entered, the stack trace is
made available to the program.
(See section 7.4, ``The try statement.'')
It is accessible as sys.exc_traceback, and also as the third
item of the tuple returned by sys.exc_info(). The latter is
the preferred interface, since it works correctly when the program is
using multiple threads.
When the program contains no suitable handler, the stack trace is written
(nicely formatted) to the standard error stream; if the interpreter is
interactive, it is also made available to the user as
sys.last_traceback.

Special read-only attributes: tb_next is the next level in the
stack trace (towards the frame where the exception occurred), or
None if there is no next level; tb_frame points to the
execution frame of the current level; tb_lineno gives the line
number where the exception occurred; tb_lasti indicates the
precise instruction. The line number and last instruction in the
traceback may differ from the line number of its frame object if the
exception occurred in a try statement with no matching
except clause or with a finally clause.

Slice objects

Slice objects are used to represent slices when extended slice
syntax is used. This is a slice using two colons, or multiple slices
or ellipses separated by commas, e.g., a[i:j:step], a[i:j,
k:l], or a[..., i:j]). They are also created by the built-in
slice()function.

Special read-only attributes: start is the lower bound;
stop is the upper bound; step is the step value; each is
None if omitted. These attributes can have any type.